Eli Schwartz

According to our database, Eli Schwartz authored at least 27 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

MAEDAY: MAE for few- and zero-shot AnomalY-Detection.

Eli Schwartz, Assaf Arbelle, Leonid Karlinsky, Sivan Harary, Florian Scheidegger, Sivan Doveh, Raja Giryes

Comput. Vis. Image Underst., 2024

Teaching VLMs to Localize Specific Objects from In-context Examples.

Sivan Doveh, Nimrod Shabtay, Wei Lin, Eli Schwartz, Hilde Kuehne, Raja Giryes, Rogério Feris, Leonid Karlinsky, James R. Glass, Assaf Arbelle, Shimon Ullman, Muhammad Jehanzeb Mirza

CoRR, 2024

Deep Phase Coded Image Prior.

Nimrod Shabtay, Eli Schwartz, Raja Giryes

Proceedings of the IEEE International Conference on Computational Photography, 2024

NumeroLogic: Number Encoding for Enhanced LLMs' Numerical Reasoning.

Eli Schwartz, Leshem Choshen, Joseph Shtok, Sivan Doveh, Leonid Karlinsky, Assaf Arbelle

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

Multispectral 3D Masked Autoencoders for Anomaly Detection in Non-Contrast Enhanced Breast MRI.

Daniel M. Lang, Eli Schwartz, Cosmin I. Bercea, Raja Giryes, Julia A. Schnabel

Proceedings of the Cancer Prevention Through Early Detection, 2023

Teaching Structured Vision & Language Concepts to Vision & Language Models.

Sivan Doveh, Assaf Arbelle, Sivan Harary, Eli Schwartz, Roei Herzig, Raja Giryes, Rogério Feris, Rameswar Panda, Shimon Ullman, Leonid Karlinsky

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Baby steps towards few-shot learning with multiple semantics.

Eli Schwartz, Leonid Karlinsky, Rogério Feris, Raja Giryes, Alexander M. Bronstein

Pattern Recognit. Lett., 2022

PIP: Positional-encoding Image Prior.

Nimrod Shabtay, Eli Schwartz, Raja Giryes

CoRR, 2022

Teaching Structured Vision&Language Concepts to Vision&Language Models.

Sivan Doveh, Assaf Arbelle, Sivan Harary, Rameswar Panda, Roei Herzig, Eli Schwartz, Donghyun Kim, Raja Giryes, Rogério Feris, Shimon Ullman, Leonid Karlinsky

CoRR, 2022

FETA: Towards Specializing Foundation Models for Expert Task Applications.

Amit Alfassy, Assaf Arbelle, Oshri Halimi, Sivan Harary, Roei Herzig, Eli Schwartz, Rameswar Panda, Michele Dolfi, Christoph Auer, Kate Saenko, Peter W. J. Staar, Rogério Feris, Leonid Karlinsky

CoRR, 2022

FETA: Towards Specializing Foundational Models for Expert Task Applications.

Amit Alfassy, Assaf Arbelle, Oshri Halimi, Sivan Harary, Roei Herzig, Eli Schwartz, Rameswar Panda, Michele Dolfi, Christoph Auer, Peter W. J. Staar, Kate Saenko, Rogério Feris, Leonid Karlinsky

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Unsupervised Domain Generalization by Learning a Bridge Across Domains.

Sivan Harary, Eli Schwartz, Assaf Arbelle, Peter W. J. Staar, Shady Abu-Hussein, Elad Amrani, Roei Herzig, Amit Alfassy, Raja Giryes, Hilde Kuehne, Dina Katabi, Kate Saenko, Rogério Feris, Leonid Karlinsky

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

MetAdapt: Meta-learned task-adaptive architecture for few-shot classification.

Sivan Doveh, Eli Schwartz, Chao Xue, Rogério Feris, Alexander M. Bronstein, Raja Giryes, Leonid Karlinsky

Pattern Recognit. Lett., 2021

ISP Distillation.

Eli Schwartz, Alex M. Bronstein, Raja Giryes

CoRR, 2021

Detector-Free Weakly Supervised Grounding by Separation.

Assaf Arbelle, Sivan Doveh, Amit Alfassy, Joseph Shtok, Guy Lev, Eli Schwartz, Hilde Kuehne, Hila Barak Levi, Prasanna Sattigeri, Rameswar Panda, Chun-Fu Chen, Alex M. Bronstein, Kate Saenko, Shimon Ullman, Raja Giryes, Rogério Feris, Leonid Karlinsky

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Fine-Grained Angular Contrastive Learning With Coarse Labels.

Guy Bukchin, Eli Schwartz, Kate Saenko, Ori Shahar, Rogério Feris, Raja Giryes, Leonid Karlinsky

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

StarNet: towards Weakly Supervised Few-Shot Object Detection.

Leonid Karlinsky, Joseph Shtok, Amit Alfassy, Moshe Lichtenstein, Sivan Harary, Eli Schwartz, Sivan Doveh, Prasanna Sattigeri, Rogério Feris, Alex M. Bronstein, Raja Giryes

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

StarNet: towards weakly supervised few-shot detection and explainable few-shot classification.

Leonid Karlinsky, Joseph Shtok, Amit Alfassy, Moshe Lichtenstein, Sivan Harary, Eli Schwartz, Sivan Doveh, Prasanna Sattigeri, Rogério Schmidt Feris, Alexander M. Bronstein, Raja Giryes

CoRR, 2020

2019

UNIQ: Uniform Noise Injection for Non-Uniform Quantization of Neural Networks.

Chaim Baskin, Natan Liss, Eli Schwartz, Evgenii Zheltonozhskii, Raja Giryes, Alex M. Bronstein, Avi Mendelson

ACM Trans. Comput. Syst., 2019

DeepISP: Toward Learning an End-to-End Image Processing Pipeline.

Eli Schwartz, Raja Giryes, Alexander M. Bronstein

IEEE Trans. Image Process., 2019

Beholder-Gan: Generation and Beautification of Facial Images with Conditioning on Their Beauty Level.

Nir Diamant, Dean Zadok, Chaim Baskin, Eli Schwartz, Alexander M. Bronstein

Proceedings of the 2019 IEEE International Conference on Image Processing, 2019

RepMet: Representative-Based Metric Learning for Classification and Few-Shot Object Detection.

Leonid Karlinsky, Joseph Shtok, Sivan Harary, Eli Schwartz, Amit Aides, Rogério Schmidt Feris, Raja Giryes, Alexander M. Bronstein

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

NICE: Noise Injection and Clamping Estimation for Neural Network Quantization.

Chaim Baskin, Natan Liss, Yoav Chai, Evgenii Zheltonozhskii, Eli Schwartz, Raja Giryes, Avi Mendelson, Alexander M. Bronstein

CoRR, 2018

RepMet: Representative-based metric learning for classification and one-shot object detection.

Eli Schwartz, Leonid Karlinsky, Joseph Shtok, Sivan Harary, Mattias Marder, Sharathchandra Pankanti, Rogério Schmidt Feris, Abhishek Kumar, Raja Giryes, Alexander M. Bronstein

CoRR, 2018

UNIQ: Uniform Noise Injection for the Quantization of Neural Networks.

Chaim Baskin, Eli Schwartz, Evgenii Zheltonozhskii, Natan Liss, Raja Giryes, Alexander M. Bronstein, Avi Mendelson

CoRR, 2018

DeepISP: Learning End-to-End Image Processing Pipeline.

Eli Schwartz, Raja Giryes, Alexander M. Bronstein

CoRR, 2018

Delta-encoder: an effective sample synthesis method for few-shot object recognition.

Eli Schwartz, Leonid Karlinsky, Joseph Shtok, Sivan Harary, Mattias Marder, Abhishek Kumar, Rogério Schmidt Feris, Raja Giryes, Alexander M. Bronstein

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018